Time-lapse images are used in a variety of applications including determining seed-lot growth rates, analyzing mechanical wear or corrosion, generating calibration signatures for oil exploration, and generating special effects for the advertising and motion picture industries.
High-quality time-lapse image sequences generation requires accurate repositioning of an imaging device relative to the subject of interest. Current techniques for repositioning imaging devices require complex and expensive hardware.
Mathematical formulae for extracting the pose (camera center and orientation relative to the scene of interest) of an imaging device are known. Multiple View Geometry In Computer Vision by Richard Hartley and Andrew Zisserman, Cambridge University Press 2000 presents a full treatment of the required math. Similar mathematical techniques are used for blending images into panoramas or steadying an image subject to camera jitter.
Current approaches for time lapse imagery, however, require highly accurate coordinate measurement devices to determine camera location relative to target. Photogrammetry techniques have been used to account for changes in position as between two images, machine vision has been used to periodically locate an image capture device but requires dedicated hardware not easily adapted to other applications (U.S. Pat. No. 5,863,984). Real time image warping has been used to correct for camera inaccuracies in camera position, yet this solution is not useful for images taken at different times (U.S. Pat. No. 6,396,961). Image alignment techniques do not address acquisition or alignment of future images (U.S. Pat. No. 6,173,087).
What is needed is a low cost, easy to use system for generating and displaying high quality time-lapse sequences. Also needed is a time-lapse image generation system that is adaptable to various imaging applications.